code: def test_device_mismatch_cuda():
      images = torch.rand(10, 3, 299, 299)
      result = InceptionModel(return_features=False, device="cuda")(
          images
      )
      assert result.is_cuda
      assert result.shape == torch.Size([10, 1000])
      result = InceptionModel(return_features=False)(images.cuda())
      assert not result.is_cuda
      assert result.shape == torch.Size([10, 1000])
  
      images = torch.rand(10, 5)
      result = DummyInceptionMetric(
          num_features=5, device="cuda"
      )._extract_features(images)
      assert result.is_cuda
      assert result.shape == torch.Size([10, 5])
      result = DummyInceptionMetric(num_features=5)._extract_features(
          images.cuda()
      )
      assert not result.is_cuda
      assert result.shape == torch.Size([10, 5])
  
file_path: ignite/tests/ignite/metrics/gan/test_utils.py
imports: from typing import Callable, Optional, Union
  from unittest.mock import patch
  import pytest
  import torch
  import torchvision
  from ignite.metrics.gan.utils import _BaseInceptionMetric, InceptionModel
label_desc: Use image node_id 6 for calling a global function with example usage: test_device_mismatch_cuda() without return types